The subject matter disclosed herein relates generally to imaging systems, and more particularly, embodiments relate to an apparatus and method for reducing image artifacts that are produced by movement of an object.
Multi-modality imaging systems exist that scan using different modalities, for example, Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), and Single Photon Emission Computed Tomography (SPECT). During operation, conventional imaging systems may exhibit image quality that is affected by motion of the object being imaged. For example, PET/CT imaging of the lung and abdomen region is generally affected by patient respiratory motion. The respiratory motion may cause an underestimation of tumor uptake and an overestimation of tumor volume.
Conventional imaging systems may utilize several methods to account for respiratory motion related artifacts. These methods include respiratory gated 4D PET/CT, deep-inspiration-breath-hold (DIBH) PET/CT, post-processing image registration methods and motion-corrected PET reconstruction. While the above methods have achieved improvements in motion correction, these methods also have certain limitations. For example, in respiratory gating, although each gated image is less affected by respiratory motion, the total detected counts are divided into several bins. Thus each gated image is much noisier than the non-gated ones. However, for patients with irregular breathing patterns with respiratory amplitude variability, the gating methods, particularly the phase gating methods, may result in unsatisfactory image quality. The DIBH PET/CT method provides a theoretically motionless image and better CT-PET match for the deep inspiration phase, however, the total acquisition time is significantly longer than that of the conventional PET/CT study if a similar amount of detected accounts are required. Image registration methods transform each gated image and sum the transformed images at the end. However, these methods significantly depend on the accuracy of the motion estimation technique used, like the widely used optical flow method, which has strict assumptions, such as intensity constraints, that are not strictly valid in PET/CT gated images.
Moreover, motion vectors may be estimated from either 4D PET or 4D CT images. However, the 4D PET images are relatively noisy and may yield an unreliable estimation. The 4D CT images are relatively low noise, but the 4D CT images are acquired during different breathing cycles from those of the 4D PET images. Thus, the motion information estimated using 4D CT images may not match that of the 4D PET images, resulting in motion estimation errors.